CompuTech’s Post

Turn distributed data into a competitive edge with #HPE Swarm Learning. 🚀 Want to learn how? Review this comprehensive white paper to find out! You'll learn what swarm learning is, how to apply it, and how it will benefit your business. 🙌 If you have additional questions, CompuTech can help.

💡 Traditional fine-tuning struggles with data distribution differences, hindering feature extraction. 🎯 Solution? Multi-source domain framework with collaborative fine-tuning for enhanced feature extraction. 💬 Join the discussion on the future of transfer learning via our widely-read preprint- https://lnkd.in/e59NrjnN #TransferLearning #AIInnovation 🤔

During the past weeks CHM Tech Global , I gained hands-on experience with predictive analytics tools, including confusion matrices for identifying errors and optimising predictions and Prophet module for financial market forecasting. Notably, I successfully installed XGBoost Regressor after initial difficulties, which reinforced the importance of persistence in resolving technical challenges. Through this process, I acquired valuable skills in predictive modeling and learned that curiosity-driven learning can lead to significant breakthroughs, ultimately solidifying my understanding of data science principles and applications. until then, print ("data science = insights + innovation")

"Thrilled to announce that I've received the APPLICATIONS & USE CASES PROFESSIONAL badge in Altair RapidMiner! 🌟 Grateful for this recognition of my dedication to mastering data analytics and excited to continue exploring new applications and use cases. Big thanks to the Altair RapidMiner community for their support and inspiration along the way! #DataAnalytics #AltairRapidMiner #ProfessionalDevelopment"

"Thrilled to announce that I've received the APPLICATIONS & USE CASES PROFESSIONAL badge in Altair RapidMiner! 🌟 Grateful for this recognition of my dedication to mastering data analytics and excited to continue exploring new applications and use cases. Big thanks to the Altair RapidMiner community for their support and inspiration along the way! #DataAnalytics #AltairRapidMiner #ProfessionalDevelopment"

🔍 Welcome to Day 8 of our #DataAnalystPrepSeries! 📊 Today, let's delve into the world of Feature Engineering! 🛠️ Feature Engineering is the art of selecting, transforming, and creating features from raw data to optimize machine learning models. By identifying relevant features, generating new ones, and transforming data, we enhance model effectiveness and accuracy. From feature selection based on correlation to creating new features through aggregation and transformation, feature engineering equips us with powerful tools for predictive analysis. 💡💻 Join the conversation: What's your favorite feature engineering technique? Share your insights! 💬 #FeatureEngineering #MachineLearning #day8

I’ve just completed the D205 - Data Acquisition Track on DataCamp! Learning a new skill was quick, interactive, and fun! Plus, everything you need is entirely in-browser. Discover which of the 500+ data and AI courses can help you build a stronger career.

Top 10 #machinelearning Algorithms

Data selection, via improving the quality of training set, helps boosting accuracy and efficiency. Our latest work studies the benefits of on-device data selection in multi-device federated learning. *paper: https://lnkd.in/dzd2rNV8 **code (on Flower Labs): https://lnkd.in/dvM-58Mn Our FL solution allows partition-based training in collaboration between constrained and resourceful devices within the client's ecosystem, which achieves ~19% higher accuracy and ~58% lower latency; compared to the baseline FL system. - work with Fan Mo, Soumyajit Chatterjee, Fahim Kawsar, Akhil Mathur